Extraction of single channel from mixed audio sample using adaptive factorization

J. Kaur, S. Gaikwad
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引用次数: 1

Abstract

In the current scenario, there exist huge amount of audio files with mixed sound sources. These mixed sounds consist of different frequencies viz. high frequency (string instruments like guitar), low frequencies (base instrument like drums, tabla) and intermediate human speech frequency. All these frequencies makes a music signal which is required for pleasure. The music creation is achieved by mixing of multiple signals using mixer. Our aim is to reverse the process of mixing and extract an audio signals so that they can be used in applications like karaoke, remix, instrumental music, audio restoration etc. One of the major application is noise cancellation and music transcription. In this paper we have demonstrated separation of single channel separation from mixed audio signal with the accuracy of 93% and average extraction speed of 20 seconds per minute of audio.
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利用自适应因子分解从混合音频样本中提取单通道
在当前的场景中,存在大量混合声源的音频文件。这些混音由不同的频率组成,即高频(吉他等弦乐器)、低频(鼓、手鼓等基础乐器)和人类语音的中间频率。所有这些频率构成的音乐信号是愉悦所必需的。音乐创作是通过使用混频器混合多个信号来实现的。我们的目标是扭转混合和提取音频信号的过程,以便它们可以在卡拉ok,混音,器乐,音频恢复等应用中使用。其中一个主要的应用是噪音消除和音乐转录。在本文中,我们证明了单通道分离与混合音频信号的分离,准确率为93%,平均提取速度为每分钟20秒的音频。
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